Stefan Jaeger, PhD
Computational Health Research Branch
Building 38A - Lister Hill Center, 10N1003O
Expertise and Research Interests:
Dr. Stefan Jaeger is a staff scientist at the Lister Hill National Center for Biomedical Communications at the United States National Library of Medicine (NLM), which is part of the National Institutes of Health (NIH). He received his diploma from the University of Kaiserslautern and his PhD from the University of Freiburg, Germany, both in computer science. Dr. Jaeger has an international research background in academia as well as in industry. He has held research positions at Chinese Academy of Sciences, University of Maryland, University of Karlsruhe, Daimler, and others. At NLM, he supervises research on deep machine learning and data science for diagnosing infectious diseases, and conducts research into image informatics and artificial intelligence for clinical care and education. His research interests include machine learning, biomedical image analysis, artificial intelligence, medical informatics, and theoretical medicine. He has more than hundred publications in these areas, several of which received best paper awards and nominations, including two patents.
Dr. Jaeger has acted as reviewer for national research councils and programs. He has served on the editorial boards of Quantitative Imaging in Medicine and Surgery, Electronic Journal of Emerging Infectious Diseases (China), and Electronic Letters on Computer Vision and Image Analysis (ELCVIA). He has also served as conference chair, keynote speaker, or program committee member for many conferences and workshops in his research area.
Honors and Awards:
- Award of Merit, National Institutes of Health, 2017.
- HHS Innovation Ventures Award, U.S. Department of Health and Human Services, 2015.
- Special Achievement Award, U.S. National Library of Medicine, 2015.
- HHS-Ignite Pathway Team Award for Automatic X-ray Screening for Rural Areas, U.S. Department of Health and Human Services, 2014.
- Certificate of Appreciation, Communications Engineering Branch, Lister Hill National Center for Biomedical Communications, 2014.
- IAPR/ICDAR Young Investigator Award Nomination, International Association of Pattern Recognition, International Conference on Document Analysis and Recognition, 2007.
- Best Student Paper, International Workshop on Frontiers in Handwriting Recognition (IWFHR), La Baule, France; Y. Li, Y. Zheng, D. Doermann, S. Jaeger. A New Algorithm for Detecting Text Line in Handwritten Documents, 2006.
- Best Paper Nomination, International Conference on Document Analysis and Recognition (ICDAR), Seoul, Korea: S. Jaeger, H. Ma, D. Doermann. Identifying Script on Word-Level with Informational Confidence, 2005.
- Research Fellowship, New Energy and Industrial Technology Development Organization (NEDO), Japan, Nov. 2000 – March 2003.
- PhD Thesis Award, German Research Centers for Artificial Intelligence, 1999.
- Daimler-Benz Graduate Fellow, Daimler-Benz Research Center, Ulm, Germany, 1994 –1998.
Publications:Yang F, Yu H, Kantipudi K, Rosenthal A, Hurt D, Antani S, Yaniv ZR, Jaeger S. Differentiating between Drug-Sensitive and Drug-Resistant Tuberculosis with Machine Learning for Clinical and Radiological Features. Quantitative Imaging in Medicine and Surgery, 0(0): 1–16, 2021. Publish Ahead of Print.
Karki M, Kantipudi K, Yu H, Yang F, Kassim Y, Yaniv Z,Jaeger S. Identifying Drug-Resistant Tuberculosis in Chest Radiographs: Evaluation of CNN Architectures and Training Strategies. 43rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, accepted on July 15th, 2021, will be held virtually October 31 – November 4, 2021.
Kassim YM, Palaniappan K, Yang F, Poostchi M, Palaniappan N, Maude RJ, Antani S, Jaeger S. Clustering-Based Dual Deep Learning Architecture for Detecting Red Blood Cells in Malaria Diagnostic Smears. IEEE J Biomed Health Inform. 2021 May;25(5):1735-1746. doi: 10.1109/JBHI.2020.3034863. Epub 2021 May 11.
Yu H, Yang F, Rajaraman S, Ersoy I, Moallem G, Poostchi M, Palaniappan K, Antani S, Maude RJ, Jaeger S. Malaria Screener: a smartphone application for automated malaria screening. BMC Infect Dis. 2020 Nov 11;20(1):825. doi: 10.1186/s12879-020-05453-1.